NORI: Fast probabilistic inference for ambiguous observation-entity mappings
Quantitative Methods
2026-05-13 v1
Abstract
NORI performs probabilistic inference to resolve ambiguous mappings between experimental observations and biological entities orders of magnitude faster than state-of-the-art methods. This makes large-scale analysis and extensive hyperparameter optimization possible, and supports a broader range of bioinformatics applications, including protein inference, taxonomic and functional analysis in omics-fields.
Cite
@article{arxiv.2605.11648,
title = {NORI: Fast probabilistic inference for ambiguous observation-entity mappings},
author = {Simon Van de Vyver and Tibo Vande Moortele and Ben-Björn Binke and Pieter Verschaffelt and Peter Dawyndt and Bart Mesuere},
journal= {arXiv preprint arXiv:2605.11648},
year = {2026}
}
Comments
8 pages, 1 table